The Book of Trees: Visualizing Branches of Knowledge has been out for six months and during this time it has received a great number of positive reviews from publications like Wired, New Scientist, Fast Company, Nature, Print Magazine, The Boston Globe, and many others. The book keeps making its rounds on Twitter and there might be a few translations coming out next year. I recently realized I never wrote a post on the underlying structure of the book, so in case you’re curious, here it is.
As exposed earlier in the year, The Book of Trees covers over 800 years of human culture through the lens of the tree figure, from its entrenched roots in religious medieval exegesis to its contemporary, secular digital themes. With roughly 200 images, the book offers a visual evolutionary history of this universal metaphor, showing us the incremental adoption of a stylized, abstract construct, as well as a recent emergence of new visual models, many employing advanced computer-generated algorithms.
The eleven chapters that compose the book feature a number of visual methods and techniques for the representation of hierarchical structures. The first (and longest) chapter features primeval tree diagrams, which bear a close resemblance to real trees and are, at times, significantly embellished. The remaining ten chapters can be grouped into two sections. The first, comprising chapters two through six, covers the earliest forms of diagrammatic, abstract tree charts and includes different types of node-link diagrams, where given nodes, entities, or “leaves” are tied across different levels by links, edges, or “branches.” The second group, encompassing chapters seven through eleven, explores more modern and recently popular approaches, showcasing various types of space-filling techniques and adjacency diagrams that use polygonal areas and nesting to indicate different ranking levels.
The book also features a Timeline of Significant Characters: key people in the establishment of the tree metaphor in depicting almost every relevant aspect of knowledge throughout the centuries. Amongst the twelve characters listed are the names of Aristotle, Joachim of Fiore, Ramon Llull, Francis Bacon, Charles Darwin, and Ernst Haeckel.
You can continue following updates on The Book of Trees on its official website or its Facebook page.
During a sumptuous dinner last February in Shibuya, Tokyo, following a long visualization workshop, my welcoming hosts presented me with a gift: an exceptional book by Japanese researcher Minaka Nobuhiros, entitled Phylogeny Mandala: Chain, Tree, and Network.
Minaka has been an avid scholar of phylogenetic diagrams, biological classification, and evolutionary science, as you can attest from the sheer number of books and papers showcased in his website. When I first discovered his work, I was extremely joyful for having found such a kindred spirit. Today, I’m very excited to announce that Minaka will be translating The Book of Trees to Japanese, to be published by BNN in 2015. I simply couldn’t hope for a more knowledgeable and qualified translator.
As many readers might have noticed, from my first and most recent book, I’m slightly obsessed with medieval information design, and the remarkable work of many our visualization forefathers, such as Isidore of Seville (ca. 560–636), Lambert of Saint-Omer (ca. 1061–ca. 1125), or Joachim of Fiore (ca. 1135–1202). An important figure in this context was the German historian and cartographer Hartmann Schedel (1440–1514). In 1493, in the city of Nuremberg, Germany, Schedel published a remarkable, densely illustrated and technically advanced incunabulum (a book printed before 1501), entitled the Nuremberg Chronicle. Also know as Liber Chronicarum (Book of Chronicles), this universal history of the world was compiled from older and contemporary sources, and comprised 1,809 woodcuts produced from 645 blocks. Some of the book’s maps were the first illustrations ever produced of many European cities and countries.
There are many online versions of this work, but if you want to get a decent, well-bound copy of this beautiful book, Taschen has recently published one that I highly recommend.
You can read more about Taschen’s copy here and here.
In the end of many of my talks, after going through a variety of compelling examples of network visualization, I wrap up with a bit of a quandary, asking the audience if there’s such a thing as a universal structure. This teaser usually comprises a side-by-side comparison between a mouse’s neuronal network and a simulation of the growth of cosmic structure and the formation of galaxies and quasars.
A common juxtaposition, shown during many of my lectures, between a neuronal network (left) and the vast cosmic structure (right).
As it turns out, this inquiry might not be as far-fetched as we might think. A few days ago, National Geographic posted an intriguing article titled Astronomers Get First Glimpse of Cosmic Web, where they report how scientists have for the first time captured a peek of the “vast, web-like network of diffuse gas that links all of the galaxies in the cosmos.” As stated in the article:
Leading cosmological theories suggest that galaxies are cocooned within gigantic, wispy filaments of gas. This “cosmic web” of gas-filled nebulas stretches between large, spacious voids that are tens of millions of light years wide. Like spiders, galaxies mostly appear to lie within the intersections of the long-sought webs.
From the original image caption in the article: Computer simulations suggest that matter in the universe is distributed in a “cosmic web” of filaments, as seen in the image above from a large-scale dark-matter simulation. The inset is a zoomed-in, high-resolution image of a smaller part of the cosmic web, 10 million light-years across, from a simulation that includes gas as well as dark matter. The intense radiation from a quasar can, like a flashlight, illuminate part of the surrounding cosmic web (highlighted in the image) and make a filament of gas glow, as was observed in the case of quasar UM287. Credit: Anatoly Klypin and Joel Primack, S. Cantalupo
This find is not just impressive and thought-provoking, but it could also become a major focus of the emerging fields of complex systems and network science.
While investigating various tree diagrams, charts, and illustrations for Chapter 1 of Visual Complexity: Mapping Patterns of Information, I became deeply obsessed with tree iconography. I remember being particularly enthralled with ancient figures from medieval Europe and three-thousand-year-old Assyrian stone carvings. During this research period, and despite my best efforts, I could never find a wide-ranging book dedicated to the tree as one of the most popular, captivating, and widespread visual archetypes. This was ultimately the crucial impetus that propelled me to create my latest work, The Book of Trees: Visualizing Branches of Knowledge.
The final cover of The Book of Trees
Trees are one of the most ubiquitous religious symbols across the world. From ancient Sumer to Christianity, from the Maya civilization to Buddhism, there’s hardly a human society over the ages that hasn’t associated trees with some sort of celestial and religious power.
The omnipresence of such a revered symbol reveals an inherently human fascination with trees that goes well beyond sacred devotion. Due to its expressive quality and natural branching scheme, trees have also become important communication tools, illustrating a variety of topics such as family ties, moral values, systems of law, domains of science, biological species, hard disk drives, database schemas, and online discussions. As a direct embodiment of hierarchy and multiplicity, the allegorical tree figure has lasted hundreds of years as one of the most enduring archetypes in the history of visual communication.
The Book of Trees covers over 800 years of human culture through the lens of the tree figure, from its entrenched roots in religious medieval exegesis to its contemporary, secular digital themes. With roughly 200 images the book offers a visual evolutionary history of this universal metaphor, showing us the incremental adoption of a stylized, abstract construct, as well as a recent emergence of new visual models, many employing advanced computer-generated algorithms. Ultimately, this book makes visualization a prism through which to observe the evolution of civilization.
Pre-order now at Amazon and take advantage of the one-time special price.
In the Preface of my new book (more details to come soon) I mention the importance of an historical analysis of visualization, since it’s critical for us to understand its long evolution and not be overly infatuated by the work created in the last decade alone. In this context I provide a quote by Michael Friendly, who stated: “There certainly have been many new things in the world of visualization; but unless you know its history, everything might seem novel.”
The tree figure is perhaps one of the most enduring, widespread visual metaphor for mapping information. With deep roots in medieval visual exegesis and illuminated manuscripts, its alluring arboreal structure has been adopted by numerous scholars, researchers, designers, and illustrators over centuries to map an incredible array of knowledge domains. Here is a simple timeline showing four distinct executions (with year below) comprising roughly a 800-year span:
But trees are not the only visual model being used for centuries. In 2001, Martin Wattenberg introduced a novel way of visualizing a song as a sequence of translucent arcs with varying width. The method showcased in The Shape of Song is better described by Wattenberg himself: “Each arch connects two repeated, identical passages of a composition. By using repeated passages as signposts, the diagram illustrates the deep structure of the composition.” The project website shows a striking gallery of images that give shape to various songs by artists such as Bach, Madonna, and Philip Glass.
This interesting technique became known as Arc Diagrams and was immediately followed by numerous projects, many of which I’ve been documenting over the years in VisualComplexity.com. Here are just some of the many visualizations embracing this approach:
However, this method is not entirely new. In fact, arc diagrams have been used for over a thousand years and were particularly popular in middle-age Europe in the depiction of, guess what, musical compositions. Many of these intricate diagrams accompanied medieval texts on musical theory and aimed at translating complex sequences of musical tones and intervals, such as tetrachords, in order to facilitate understanding. They were ultimately educational tools meant to be attentively studied and analysed.
Here are some remarkable examples:
But from all the cases I found, the double-page chart below from a 13th-century manuscript is arguably one of the most complex and intricate examples of this old technique. A great specimen of medieval visual exegesis that served as a teaching tool for musical theory, this graph represents the various divisions of a monochord–an ancient single-string musical instrument.
* Ancient arc diagrams from: Murdoch, John E. Antiquity and the Middle Ages. Vol. 5 of Album of Science. New York: Scribner, 1984.
As one of the most hailed methods of modern information visualization, the treemap has truly become an epitome of the recent growth of the field and one of the most widespread methods for visualizing hierarchies. Credited with inventing the method in 1991, when trying to find an optimal solution to visualize the file structure of his hard drive, Ben Shneiderman’s contribution is invaluable, opening the door to a great diversity of novel approaches, such as the circular and voronoi treemaps. Here’s a screenshot from one of the earliest modern treemaps:
Shneiderman is certainly the father of the modern, computer-generated treemap, which introduced an important recursive tilling algorithm able to handle large, multi-level hierarchies. But the concept was not entirely groundbreaking. Area diagrams and simplified rectangular treemaps had been in use for several decades before Shneiderman’s preeminent work.
The image below shows a comparative diagram showing the size and population of each continent and country of the world, part of a world atlas compiled in 1845. This is a four-level treemap, where the world (1) is comprised of three major “continents” (2), divided into regions (3), and further subdivided into individual countries (4).
The following chart is perhaps known to some of you, since it has surfaced in a few places in print and online like Fast Company. It is not only one of the earliest examples of a rectangular treemap, but also makes a compelling use of the small multiples technique.
Old Visual Metaphors
As with many other contemporary visualization techniques, the previous examples show us that the roots of arc diagrams and treemaps are considerably deeper than what they seem. Even though I only explored two visual methods in this post, a similar analysis could easily embrace many other present-day models. Others, such as hyperbolic trees, seem to be genuinely digital-native, given it’s dynamic exploration of hyperbolic space and reliability on human-computer interaction. Still, their unmistakable predecessors - radial trees - have been in use for several decades, and many researchers and artists, most notably E. C. Escher, have throughly investigated hyperbolic geometry in their work.
The goal of this post is not to devalue the contribution of main figures in modern information visualization, nor to provide a negative everything-has-already-been-invented attitude. Above all, it is to recognize the ancient evolution of this discipline and the achievements of the past, to understand their origins, progress, challenges, failures, and successes. As Mark Twain appears to have said: “History doesn’t repeat itself, but it does rhyme.”
The recent app for Citi Bike in NYC features a smart, effortless visual indicator for bike stations that is quite successful. They could have done this little icon in several different ways: perhaps a simple static icon featuring the number of available bikes/docks for each station that when tapped would provide additional information. Instead, they explored a glass full/empty analogy (or hourglass metaphor) in a way that is playful, efficient, and understandable at a glance. Plus it is fed by live dynamic data. The pins that are “filled-up” with dark blue have more available bikes (better for picking them up), versus the cyan “empty” ones that have more available docks (great for dropping them). A simple execution that made me smile.
The power of graphics, and particularly the alluring quality of the circle, has once again been appropriated to communicate a critical, much-needed theory. Oxfam senior researcher and former co-author of the UN’s annual Human Development Report Kate Raworth has introduced a popular diagram that integrates a series of planetary boundaries with a set of social responsibility elements. This image has become so popular that it’s currently driving the emergence of a new label called “Doughnut Economics”. This phenomenon is not necessarily new. There are numerous examples of a specific graphic model having such a powerful influence that it becomes the ultimate epitome of the underlying concept. Think about Darwin’s Tree of Life or the Copernican model. This occurrence seems to corroborate the general principle of a successful information graphic: have a strong/unique underlying thesis or point of view. Here is the image that’s generating such a buzz:
You can also see below an insightful talk by Raworth at the Royal Society of Arts where she explains the theoretical framework behind the image.
“I’m really stoked by the traction this diagram has had […] and I’m asking myself why?”, stated Raworth during her talk, and she then exposed three reasons to explain the diagram’s recent popularity (in her own words):
(1)The framing of planetary boundaries is a very very powerful one, it makes the complexity of earth system science accessible to non-scientists and helps us to see the planet as a whole, as a system of interlocking processes that we depend upon for our well-being.
(2)By putting that social foundation in the heart of it, it brings into one simple picture the world of development and the world of environment, and it helps to end the false dichotomy that we face that either you are for development and ending poverty, or you are for protecting the environment (…)
(3)People are interested in it because it gives us a chance to rethink economic development, instead of starting with economic growth, we start with the fundamentals of what we care about (…)
In November 2011, I wrote a post on the recent and astonishing popularity of these long graphical strips, commonly known as infographics. In the same post I showed 42 samples that people submitted to Visual Complexity over the period of roughly a year (see sample below).
It’s particularly interesting to recall that less than four years ago the term infographic used to cover any type of chart, graph, diagram, histogram, table or illustration conveying a specific data attribute. We called it simply, an information graphic. But over the past few years, the expression has become closely associated with a long vertical table encompassing a variety of graphical elements, such as maps, uncanny clip art, miscellaneous charts, large text and bulky numbers. This association is currently so strong that it seems almost impossible to keep the two concepts apart. Consequently, the recent outburst of popularity of infographics has caused the emergence of various companies dedicated almost exclusively to the production of this type of graphic for private clients, institutions, blogs, and mainstream media; making it arguably one the strongest economic forces within the information design landscape.
But as with many other types of contemporary graphics, the idea in itself is not entirely novel. The papyrus roll from Ancient Egypt, the direct ancestor of the modern book, is conceivably also the ancient forefather of modern infographics. Consisting of papyrus sheets pasted edge to edge with a slight overlap, the text and graphics was set out in columns, and drawn up at right angles to the edge of the rolls. Even though most papyrus were meant to be read from left to right, unrolling them as the reader went along, some also explored a vertical top-down linear narrative. This concept was further propelled across Middle Age Europe, where scholars were at loss trying to integrate all the new knowledge coming from the ancient world, and biblical exegesis was evolving from a simple allegorical division to a complex analytical process. During this stage we can witness a variety of parchment scrolls employing a diagrammatic representation of biblical tales, family trees, systems of law, knowledge maps, amongst many other topics. On the left we can see two compelling medieval specimens. The first on the left is a small part of a remarkable genealogy of Christ from circa 1130-1205, while the second is a depiction of the genealogical tree of the House of Habsburg, circa 1540.
But out of all the cases I’ve seen in the past, the chart below is perhaps one of the best examples of a prototypical infographic and a strong progenitor of such a concept, abundantly explored in the last few years. This 19th century piece is showcased in the magnificent book The Cartographies of Time, published by Princeton Architectural Press in 2010.
Printed by Joshua Himes in 1842, A Chronological Chart of the Visions of Daniel and John, integrates the visual logic of the timeline, chronological calculus and apocalyptic symbolism in a single scheme. The final date in the left-hand column, 1843, indicates the coming of the end of the world. As BibliOdyssey explains in a post: “This infographic is based on the religious revivalist predictions of the New England minister, William Miller. From the 1830s, Miller’s followers produced stirring books, pamphlets, broadsides and innovative graphics to spread the word of the coming apocalypse, often displayed and distributed at popular camp meetings.”
The resemblance with modern-day infographics is primarily based on three features: (1) The portrayal of a specific story or topic in a long top-down graphical layout. (2) The use of specific illustrations or clip art (in the case of present-day versions) with complementary text to better elucidate the various components of the subject. (3) The inclusion of large numbers to convey specific quantities pertaining to the analyzed topic.
Here’s a comparison of the 1834 chart next to two modern infographic approaches:
About two years ago, in November 2010, I wrote a post stating I much I enjoyed and admired the “remarkable examples of visual storytelling” produced by the Royal Society of Arts (RSA) and CognitiveMedia in their enticing RSA Animate series. Earlier this year I received an email from RSA telling me that they were considering turning my original RSA talk, from December 2011, into an RSAnimate. I was absolutely over the moon. In May 2012, the 12th video of the series was released, based on my talk “The Power of Networks“. The final result exceeded all my expectations, and to this day I’m still dumbfounded by the phenomenal creativity of Andrew Park and his team, and the fantastic visual metaphors they continuously come up with.
Apart from the video you can also download a pdf of the complete final drawing, or order a printed A0 poster (well worth it). Here are some images of the final composition:
**This text was part of an extinct chapter of Visual Complexity: Mapping Patterns of Information, which never saw the light of day. Instead of being forgotten in a dusty folder, I decided to make it available to the general public and invite any constructive criticism by our growing community. Hope you will find it useful.**
Data and information visualization are fundamentally about showing quantitative and qualitative information so that a viewer can see patterns, trends, or anomalies, constancy or variation, in ways that other forms – text and tables – do not allow.
The concept of visualization is certainly not new. Humans have been involved in the visual representation of information for more than 30,000 years. During this time, there has been a variety of portrayed subjects, many of them pertaining to natural phenomena, but the common underlying purpose of communicating a message has always been present. Whether we talk about cave paintings, cuneiforms, maps, or charts, we are always alluding to information in a quality of a message from a sender to one or more receivers. “The progress of civilization can be read in the invention of visual artifacts, from writing to mathematics, to maps, to printing, to diagrams, to visual computing.”, say Card, Mackinlay and Shneiderman. Historian Alfred W. Crosby attests to the importance of visual aids throughout the ages, by claiming that visualization and measurement were the two factors most responsible for the rapid development of all of modern science.
Even though visual artifacts have always been a central element in the history of humankind, over the last 25 years the term “visualization” has become immensely popular, being fragmented in a profusion of subfields, carrying a diversity of specialized labels such as Information Visualization, Data Visualization, Scientific Visualization, Software Visualization, Geographic Visualization, Knowledge Visualization, Flow Visualization, and even Music Visualization. Many of these areas emerged in the midst of existing parallel areas like Information Design, Information Graphics, and Visual Communication. The distinction between them is occasionally thin, and in some cases almost inexistent. This rich plethora of labels is certainly indicative of the outburst of a new practice, but one that is still struggling to define itself. While some consider this to be the birth of a new medium, or even a new science, the consensus on a definite descriptive label is not so obvious.
According to Michael Friendly, the renowned professor of Psychology at York University in Canada, information visualization is the broadest term that could be taken to include all the developments in visualization, since “almost anything, if sufficiently organized, is information of a sort: tables, graphs, maps and even text, whether static or dynamic, provide some means to see what lies within, determine the answer to a question, find relations, and perhaps apprehend things which could not be seen so readily in other forms.” But even able to accommodate the broadest of scopes, information visualization has also been the definite title of a multidisciplinary field emerging out of the computer science community in the late 1980s.
Originally coined by Jock Mackinlay and his User Interface Research Group at Xerox PARC in 1986, information visualization relates to the “use of computer-supported, interactive, visual representations of abstract data to amplify cognition”. It’s in essence a computer-driven transformation of abstract data (distinct from physical data – the earth, molecules, cells, human body, etc) into an interactive visual depiction aiming at insight – which in turn translates into “discovery, decision-making, and explanation”. Congregating a vast body of research from computer science, human-computer interaction, communication design, cognitive psychology, semiotics, statistical graphics, cartography, and art, modern information visualization surfaced from advances in computer graphics and was further consolidated in 1987, when the NSF Panel on Graphics, Image Processing, and Workstations published its landmark report Visualization in Scientific Computing. Since then, information visualization has grown considerably as an independent discipline, fostered by many conferences and workshops dedicated to the topic, particularly the prominent IEEE Computer Society symposium on Information Visualization, known as the InfoVis conference, first held in 1995.
With roughly two decades, information visualization has already been the target of some criticism and dismissal. Most of it comes from an inadequacy of the field to swiftly adapt to recent changes, caused by a large adoption from eager art and design communities and an escalating curiosity from media, advertising, and publishing. As a close-knit group, naturally inclined towards the computer science community, as a result of its own heritage, information visualization must take a stance to either adjust to these changes and fully accept its growing popularity, or instead, remain a niche inward-looking academic practice. Some signs of an embrace between traditional circles and the new wave of enthusiasts are already starting to surface, and this initial hesitation might simply go down in history as the normal shyness of a first date. Nonetheless, it is not surprising that under the present uncertainty, some voices have come forward suggesting new terms and definitions. Ben Fry in his PhD thesis defended a new label called “Computational Information Design”, able to properly integrate information visualization, data mining and graphic design, while Robert Kosara is a promoter of “Visual Analytics”, with a stronger emphasis on analytical reasoning. While many of the arguments for new labels reinforcing specific scientific or design concerns are certainly valid, there’s a major concern of an excessive breakup of a field that’s still defining itself.
Instead of trying to devise new titles for alternative branches highlighting a particular area of focus, the effort should be in creating a bridge between the existing body of research and the abundance of novel demands, in an attempt to revise and renovate the field, steering information visualization into a mature, integrated, and in demand hotspot. If willing to adapt, the field is broad enough to fully encompass most requirements, from a stronger prominence of design to a reinforced attention to analytics. This doesn’t mean the discipline can incorporate any attempt at visualizing data. But in essence, all interactive visual representations, able to make the depicted subject more intelligible and transparent, or find a new explicit insight within it, can and should be embraced by information visualization.
Information visualization is well known for its multidisciplinary nature, assembling people from a vast assortment of backgrounds, but notwithstanding the contribution of innumerous disciplines, we can still highlight three main spheres of activity that best characterize its key attributes and capabilities. Readers familiarized with research publications in the field will find this conception slightly different from previous frameworks developed by Stuart Card, Jock Mackinlay, Ben Shneiderman, and Ed Chi. The deliberate intent of this reframing is to emphasize the leading role of design, in both visual and interactive choices, and the fundamental function of statistics and data mining. This is ultimately an integrating, yet diverse framework, keeping alive the heterogeneous nature of the discipline. Here we describe the three central layers of information visualization: Data Transformation, Visual Mapping and Interactive Framing. Even though there’s a natural progression between the three stages that doesn’t mean they sustain in a fixed order. There’s a lot of refinement taking place in a continuous iterative process that forces each step to be occasionally revisited.
This is the very first stage in the development of any information visualization project. Without data no visualization would even be possible, hence everything starts by attaining access to a particular dataset relevant to the project’s pursuit. After getting hold of the data, what follows is a long process of data analysis, which includes inspecting, cleaning, filtering, and parsing the data, while organizing the relevant parts and removing the irrelevant. The subsequent process of data mining is crucial in order to have a better understanding of the natural affordances of the dataset. It encompasses a series of queries and algorithms in order to extract particular patterns in the data for some quick modeling and visualization tests, which will be of great importance in the build up of the second stage. Data transformation is the essential foundation of a successful execution, and covers areas like programming, statistics, data analysis, data mining, analytics, and machine learning.
Visual mapping is a critical step in information visualization, where data finally comes to life through a deliberate visual form. It takes into consideration key factors like top-to-bottom hierarchy, color, legibility, typeface, contrast, spacing, position, size, shape, orientation, layout, and depth. This central task contemplates not only individual views or modules, but also the composition of the entire contiguous environment. The choice of a particular method (or methods) is tied with the specific goal of the piece – its intrinsic purpose – and might be defined a priori or during project development, as the natural affordances of the data come into place. It’s also highly dependent on end users, their immediate context and expressed needs – when, where, and how the final execution will be used. Visual mapping is tied with various areas of visual design, including graphic design, information design, interface design, visual perception, cognitive psychology, aesthetics, and typography. Furthermore, it’s essentially made of two components: graphical objects and textual objects.
Information visualization is ultimately a discovery tool, and interactivity provides the final coalescing layer for exploration. “Visual representations and interaction techniques take advantage of the human eye’s broad bandwidth pathway into the mind to allow users to see, explore, and understand large amounts of information at once”, elucidate James Thomas and Kristin Cook, and they further explain, “Visual representations alone cannot satisfy analytical needs. Interaction techniques are required to support the dialogue between the analyst and the data. While basic interactions such as search techniques are common in software today, more sophisticated interactions are also needed to support the analytical reasoning process.”
Some don’t see the clear-cut need for interaction in information visualization, so it’s important to clarify this assertion. In a broader definition of visualization, it’s broadly consensual that information can be successfully conveyed in either static or interactive executions. However, we have to question what really sets information visualization apart from other parallel fields such as information design or information graphics. It’s in fact its computer-supported interactive nature that truly makes it distinct, and this unique offering becomes imperative as the degree of complexity of the portrayed system increases. The representation of complex networks is just an instance where interactivity is vital. Coupled with a relevant time-variant dataset, interactivity can also be a critical driver in a shift from short-term casual engagement to long-term active engagement, substantiating information visualization as a significant tool for exploration.
But interactive framing is not limited to the constraints of a computer screen. It covers any responsive visualization where a two-way communication between user and layout is established, from reactive surfaces to highly immersive visualization environments. This ultimate unifying layer is critical for explorative analysis, enabling users to inquire, filter, manipulate, reshape, and examine the visual outcome in order to identify properties, relationships, regularities, or patterns. Finally, it’s important to elucidate that even though interactivity is a central component of information visualization, the field doesn’t aim at replacing static depictions of information, since they can successfully complement each other. It simply provides an alternative, yet extremely powerful medium.
Even though there is a widespread consensus on its qualifications, information visualization, as a recent emergent field, still lacks a structural foundation able to uphold and expand its projection well into the future. We cannot consciously claim to be a new medium or a new science, when innumerous questions are still unresolved. It is critical for such an introspection effort to happen without delay, since there’s too much work to be done, and once we all agree on what we do as a community, it will be easier for external parties to recognize the goals and boundaries of our discipline. It’s obvious that we are still pulling together the different parts that make this practice and trying to understand when best to use them, but in order for information visualization to take the next step, and grow into a cohesive field of study, it requires the consolidation of three critical components:
Assemble a clear underlying theory able to combine many of the learnings, knowledge and insights from the variety of disciplines that make information visualization. If recent years have been marked by a significant profusion of new projects, this sturdy practice needs to be sustained by a reliable system of ideas and ideological principles. The purpose is to ultimately provide a broad consensual framework able to evaluate past, present and future endeavors. The current unguided exploration is by no means detrimental, since it’s the perfect setup for innovation to sprout, however, if the discipline wishes to mature as a reliable knowledge domain, it needs a supporting body of theory capable of accommodating all recent advances. Cognitive psychology might be one of the most reliable instruments in the edification of such a system, able to easily translate cognitive behaviors into objective design principles. A theory of information visualization will have to embrace diversity, and consequently several theories might need to coexist in opposition to one universal all-encompassing framework.
Define the spectrum of representational methods and techniques of information visualization. The central aim should be to consolidate and further exemplify, by recognizing the different data types and structures that underlie a common typology of patterns. Chaomei Chen, an important figure in the field, asserts on this current call to arms: “a taxonomy of information visualization is needed so that designers can select appropriate techniques to meet given requirements”. This is not meant to be a fixed and definite taxonomy, but an evolving, ever-growing, ever-expanding endeavor. This effort doesn’t contemplate a mere collection of techniques either; it should foremost supply a set of foundational principles able to guide present and future practitioners. Some initial steps in the description of common information visualization patterns have started to arise, but we still have a long way to go.
Provide easy evaluation methodologies for existing tools and approaches. Information visualization requires a common rule system that can accordingly distinguish the good from the bad, the appropriate from the inappropriate, the usable from the unusable, the effective from the ineffective. Case studies and success stories are a great first step in this direction. If information visualization is a vehicle for evidence and clarity, it should embrace the same ideology in the definition of its own practice, by creating a systematic body of analysis able to properly evaluate the success of any project. Quantitative and qualitative evaluation methods should be welcomed, including observational studies, participatory assessment, usability testing, contextual interviews, and user feedback. This effort should, most importantly, go hands in hands with the development of an adequate language of criticism.
In the Preface of Visual Complexity: Mapping Patterns of information, I exposed my astonishment with the amount of dead links and error messages encountered while reviewing projects to feature in the book. It’s therefore not surprising that preserving many of these projects for posterity became a central drive for the book’s completion. This took an even more serious tone when I started digging deeper into an unsettling prospect commonly referred to as the Digital Dark Age. This expression essentially contemplates a future scenario where it will be difficult or impossible to read historical documents or artifacts, because they have been stored in an obsolete digital format. Even though this is a widespread dilemma of modern technology, affecting a variety of knowledge domains, when it comes to information visualization, the possibility of many present-day digital projects vanishing within a few decades is a considerable worrying prospect.
As I researched many of the projects to showcase in the book, I was surprised to find that it was easier to retrieve an illustration from Joachim of Fiore, produced 800 years ago, than to attain an image of a visualization of web routers, developed in 2001. As I expressed in the Preface:
The reasons for the disappearance are never the same. In most instances, pieces are simply neglected over time, with authors not bothering to update the code, rendering it obsolete. In other cases, the plug-in version might become incapable of reading older formats or the API from an early dataset source might change, making it extremely difficult to reuse the code that generated the original visualization. Lastly, projects are occasionally moved into different folders or domains or just taken down from the servers, simply because they highlight an outdated model that does not fit the current ambitions of their respective author or company.
Just yesterday while researching for meaningful tree visualizations, the project Ecotonoha came to mind, as it always does, so many times I lost count. Sponsored by NEC and developed by Yugo Nakamura in 2003, Ecotonoha was a project to nurture a virtual tree collaboratively, and at the same time contribute to the actual environment to cope with global warming. More important, Ecotonoha has been a major inspiration for several artists/designers over the last decade and influenced numerous new media projects. If you try to access its website today, there’s a simple message that reads:
The Ecotonoha campaign launched in 2003 has come to an end. We thank you very much for participating in this initiative. During the campaign, 7,423 trees were planted based on messages generated. We believe that your messages in shape of these trees will contribute greatly to sustaining the earth. We hope to have your continued support in our activities and to the conservation of the earth.
But Ecotonoha is a success story in the current landscape. Most online visualization projects have a much shorter lifespan, and very few will reach Ecotonoha’s milestone of 8 years. Overall, this digital laissez-faire contributes to the ephemeral nature of most online artifacts, and consequently the whole field suffers from memory loss.
New York Times - Timelapse
A few months back I saw a canny post by Philip Vieira, which made me rethink about the dangers of our current digital laissez-faire. Due to an errant cron task that ran twice an hour from September 2010 to July 2011, Philip Vieira, a developer based in Toronto, Canada, accidentally collected 12,000 screenshots of the front page of the nytimes.com. With this rich content at hand, Philip created a time-lapse video showing the dinamic, ever-changing nature of the New York Times online frontpage over months. The result was utterly fascinating and absorbing, but it also led Philip to equate how how much is being lost, every minute of the day, across numeral digital artifacts.
As Philip Vieira expresses on his post:
Having worked with and developed on a number of content management systems I can tell you that as a rule of thumb no one is storing their frontpage layout data. It’s all gone, and once newspapers shutter their physical distribution operations I get this feeling that we’re no longer going to have a comprehensive archive of how our news-sources of note looked on a daily basis.
His concern is valid and entirely in line with mine:
This, in my humble opinion, is a tragedy because in many ways our frontpages are summaries of our perspectives and our preconceptions. They store what we thought was important, in a way that is easy and quick to parse and extremely valuable for any future generations wishing to study our time period.
Of course many others are also concerned with the prospect of a Digital Dark Age. In October 2010 the exhibit Digital Archeology opened in London as part of Internet Week Europe, with the primary purpose of harvesting and uncovering dozens of websites created in the last 20 years. As the organizers state on their website:
Over this short time, technological and communications developments have been so fast that the groundbreaking work of the early creative pioneers, produced on now defunct hardware and software, have disappeared almost as soon as they appeared, like Mayflies in spring doomed to die as the daylight fades.
Concerned that “the evidence of this explosion of creativity may be consigned to digital oblivion”, this exhibit is timely and extremely relevant:
Soon we will know less about these HTML blossomings than we do about the relief carvings in Mohenjo-Daro or the Yucatán. While they helped define our new culture, almost none of the websites of less than two decades ago can be seen at all. Today, when almost a quarter of the earth’s population is online, this most recent artistic, commercial and social history is being wiped from the face of earth and a hundred million hard drives lie festering in recycling yards or rusting in landfills.
The Deleted City
Another recent, and even more evocative project on this topic is The Deleted City. The installation is an interactive visualization of a 650 gigabyte backup of Geocities made by the Archive Team on October 27, 2009. It depicts the file system as a city map, spatially arranging the different neighborhoods and individual lots based on the number of files they contain. As the authors explain:
Around the turn of the century, Geocities had tens of millions of “homesteaders” as the digital tennants were called and was bought by Yahoo! for three and a half billion dollars. Ten years later in 2009, as other metaphors of the internet (such as the social network) had taken over, and the homesteaders had left their properties vacant after migrating toFacebook, Geocities was shutdown and deleted.
In an heroic effort to preserve 10 years of collaborative work by 35 million people, the Archive Team made a backup of the site just before it shut down. The resulting 650 Gigabyte bittorrent file is the digital Pompeii that is the subject of an interactive excavation that allows you to wander through an episode of recent online history.
The need to preserve
Today there are numerous cuneiform records - one of the earliest known forms of written expression, some 6,000 years old - which communicate a great number of insights about Sumerian, Assyrian, and Babylonian cultures and societies. Can we safely guarantee that some, if any, modern-day digital artifacts will last this long?
I’m not surprised by the news of Amazon’s e-book sales surpassing printed ones, or by any recent story on the conversion of atoms into bits. As Benny Landa once said in respect to this inevitable progress: “Everything that can be digital, will be”. I’m not concerned with mass digitization, I’m simply fearful we are not making enough effort to preserve it. After all, what good is all this information if we cannot safely guard it for future generations?
Many readers of Visual Complexity: Mapping Patterns of Information have been wondering about the cover design and its underlying meaning. Since there’s no information about the piece in the book, primarily due to an oversight that will be fixed in a following edition, here’s a bit of an explanation.
I always wanted to feature a visualization or bespoken illustration in the cover, and it would have to be something related to the book and its content. Talking to a friend of mine a while back, the idea of creating a piece based on the book’s body of text came up. I thought that was definitely the way to go and started looking closely at some of my favorite textual visualizations out there.
It took me a while to decide on the appropriate style and method I wanted to feature, but then I payed a closer look at the amazing work of Boris Müller. For those who are not familiar with his work, Boris has created many great projects in the past, including Connected Communities and Knowledge Maps. But I have always been particularly impressed by his remarkable Poetry on the Road series. Since 2002, Boris has been commissioned to design a visual theme for the Poetry on the Road international literature festival, which is held every year in Bremen, Germany. For the various editions of the festival, Boris has created a poster with rich visual graphics generated by a computer program that turns selected poems of the participants into striking compositions. Every year has a different theme, and some are truly outstanding (e.g. 2003, 2006).
When I approached Boris to do something similar for the cover of Visual Complexity he was immediately on board. He ended up providing a simple java app that could be used with any text to generate a similar visual output to the one he created for Poetry 2008. I started playing around with it and this was the very first set of experiments:
There was still no information on the cover, it was pure visual exploration at this stage. I started by depicting individual chapters, simply because it was more manageable and easier to grasp the type of outcome provided by the app. Below is a second group of tryouts using different colors and including the title and author’s name.
In order to reveal a bit more diversity, we also explored different colors in the same composition and one unique visualization featuring all seven chapters of the book.
Finally, and after a long discussion between myself and the design and marketing departments at Princeton Architectural Press, we finally agreed on the last version of the cover, this one including the entire seven chapters, or roughly 35,558 words. The final printed outcome has exceeded my expectations and sometimes it is easy to forget how much time, sweat, love, and dedication goes into a book cover.
In case you are still wondering how everything works, here’s an extended description to be featured in a later edition of the book:
“Visualization featuring all 35,558 words displayed in the entire book, spread across its seven chapters. It was built by sorting all words based on their frequency in the text and representing them as lines. Lines are grouped in seven horizontal bands, representative of all chapters, from top to bottom, chapter 1 to chapter 7. Thicker lines depict most frequent words, which are placed on the left hand side of the diagram. As words are repeated across different chapters their lines flow vertically from one band to the other.”
Here is a close-up of the final product:
And the book being displayed in two bookstores in NYC, respectively Strand (left) and St. Mark’s (right):